期刊
WEATHER AND FORECASTING
卷 35, 期 6, 页码 2589-2602出版社
AMER METEOROLOGICAL SOC
DOI: 10.1175/WAF-D-20-0029.1
关键词
Stratospheric circulation; Ensembles; Forecast verification/skill; Hindcasts; Seasonal forecasting; Tropical variability
资金
- National Center for Atmospheric Research - National Science Foundation [1852977]
- NOAA's Climate Program Office (CPO) Modeling, Analysis, Predictions and Projections (MAPP)
- Regional and Global Model Analysis (RGMA) component of the Earth and Environmental System Modeling Program of the U.S. Department of Energy's Office of Biological and EnvironmentalResearch (BER) via National Science Foundation [IA 1844590]
- NOAA Climate Program Office Climate Variability and Predictability Program
- NSF [AGS-1652289]
- KMA RD Program [KMI2018-03110]
- NOAA/OWAQ [SPC-000940]
- NOAA/MAPP [NA16OAR4310146]
There is a growing demand for understanding sources of predictability on subseasonal to seasonal (S2S) time scales. Predictability at subseasonal time scales is believed to come from processes varying slower than the atmosphere such as soil moisture, snowpack, sea ice, and ocean heat content. The stratosphere as well as tropospheric modes of variability can also provide predictability at subseasonal time scales. However, the contributions of the above sources to S2S predictability are not well quantified. Here we evaluate the subseasonal prediction skill of the Community Earth System Model, version 1 (CESM1), in the default version of the model as well as a version with the improved representation of stratospheric variability to assess the role of an improved stratosphere on prediction skill. We demonstrate that the subseasonal skill of CESM1 for surface temperature and precipitation is comparable to that of operational models. We find that a betterresolved stratosphere improves stratospheric but not surface prediction skill for weeks 3-4. SIGNIFICANCE STATEMENT: There is a growing demand in society for understanding sources of predictability on subseasonal to seasonal time scales. In this work we demonstrate that the CESM1 research Earth system model can be utilized as a subseasonal prediction model and show that its subseasonal prediction skill is comparable to that of operational models. We also show that the inclusion of a well-resolved stratosphere does not improve the subseasonal (week 3-4 averaged) forecast of temperature and precipitation at the surface.
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